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authorJustin Bedo <cu@cua0.org>2020-12-03 15:20:28 +1100
committerJustin Bedo <cu@cua0.org>2020-12-03 15:20:28 +1100
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wehi announcement
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+Title:
+
+BioNix: functional, reproducible bioinformatics workflows
+
+Abstract:
+
+A challenge for computational biologists is to make our analyses
+reproducible - that is, easy to rerun, combine, and share, with the
+assurance that equivalent runs will generate identical results. Current
+best practice aims at this using a combination of package managers,
+workflow engines, and containers.
+
+In this talk I will present BioNix, a lightweight library built on the Nix
+deployment system. BioNix manages software dependencies, computational
+environments, and workflow stages together using a single abstraction:
+pure functions. BioNix lets users specify workflows in a clean, uniform
+way, with strong reproducibility guarantees.
+
+I will also discuss the application of BioNix to the Stafford Fox Rare
+Cancer project. Within this project BioNix has been used to manage a
+complicated workflow across >100 whole genome and whole exome sequences. I
+will discuss lessons learnt from this application and the future direction
+of BioNix.
+
+Bio:
+
+Dr Justin Bedő is the Stafford Fox Centenary Fellow in Bioinformatics
+and Computational Biology for Rare Cancers at the WEHI. He was awarded
+a PhD by the ANU in 2009 in Machine Learning. His PhD investigated novel
+machine learning algorithms to solve bioinformatics problems arising
+in plant breeding and cancer genomics. After his PhD he obtained
+Postdoctoral experience at NICTA and IBISC (Genopole, Paris) as well as
+industrial research experience at IBM Research Australia. His interests
+span machine learning, diagnostic genomics, and bioinformatics.